Wednesday, 11 November 2015

This is SET-5, to read from start click here This set contain top 10 tableau interview questions answer.
Our last article is about Power BI Interview Questions , powerBI growing very fast these days, So If you are preparing for Tableau then must through PowerBI Interview questions as well, because interviewer can ask some question related to PowerBI.

TOP TABLEAU INTERVIEW QUESTIONS FOR FRESHER AND EXPERIENCED

41). How are the Tableau Personal and Professional, different from each other?
Ans: Personal is the same as Professional except:
1. Personal only connects to flat files (Excel, Access, CSV, and Tableau Data Extract.)
2. Personal can't publish to Server.

42). Can Tableau Desktop be install on a Mac OS?
Ans: Yes, Tableau Desktop can be installed on both Mac and Windows operating systems.

43). What API support does Tableau offer?

Tableau Data Extract API: Create a program to bring data from a non-supported data source into Tableau. The program will automate Tableau Data Extract data-source creation.

45). What is the difference between "Connect Live" and "Extract"?
Ans: Connecting Live: Connecting Live to a database leverages its computational processing and storage. New queries will go to the database and are reflected as new or updated within the data.
Extract: An Extract will make a static snapshot of the data to be used by Tableau's data engine. The snapshot of data can be refreshed on a recurring schedule as a whole or incrementally append data. One way to set up these schedules is via Tableau Server.

46). What's the maximum number of rows Tableau can utilize at one time?
Ans: Tableau is not restrained by the number of rows in a table.
Customers use Tableau to access petabytes of data because it only retrieves the rows and columns needed to answer your question. Let me share some customer use cases focusing on big data.

47). What is the Tableau data engine?
Ans: Data engine is really a cool feature of Tableau. It's an analytical database designed to achieve instant query response, predictive performance, integrate seamlessly into existing data infrastructure, and is not limited to loading entire data sets into memory. If you work with a large amount of data it takes some time to import, create indexes and sort data but after that every thing speedup. Tableau data engine is not really in-memory technology. The data is stored in disk after imported and then RAM is hardly utilized. This conception brings the desired performance.

48). A Customer can't connect to their data. What is the procedure to set them up for a solution?
Ans: Have the customer share the error message they're receiving with you and Tableau's technical support. Try to troubleshoot the error on the fly, but if you also want to completely solve the issue. Schedule additional support if needed.

49). What is Metadata in Tableau?
Ans: Data that describes other data.
Meta is a prefix that in most information technology usages means "an underlying definition or description." Metadata summarizes basic information about data, which can make finding and working with particular instances of data easier.

50). What are semantic layers?
Ans: Semantic Layers are a business representation of corporate data that helps end users access data autonomously using common business terms.
Simplifying complex data into familiar business terms such as product, customer or revenue.